Workshop: Pitcher Injury Factors

by
June 18, 2020

Projecting pitcher injuries and their effect seems like the Holy Grail for fantasy analysis. From years of research on the subject, I find it’s just a frustration filled enterprise with no firm resolution. Until a start to the 2020 season has been agreed upon (or I eventually find an acceptable answer), I plan to continuously grind for a workable understanding of pitcher injuries.

First, this article will be a work in progress as I try to find answers to various questions. I can’t fill the RotoGraphs article list with a new article every time I make a change or add more information (Ed. note: Sure you can, Jeff, we’ll post all of ’em!). Every few days or so, I’ll summarize the findings from the previous article’s work and keep moving forward. The series will come to an abrupt end if the framework exists for a start to the season since other analysis will then take priority.

I’ve started down this path already with a couple of recent articles on pitcher injuries. Here is a summary of the findings:

  • Accumulation of previous IL days leads to increase aging and injuries compared to other pitchers.
  • Accumulation of arm injuries leads to increase aging and injuries compared to other pitchers.
  • High fastball velocity leads to an increase in injuries compared to those who throw slower.
  • Age doesn’t seem to be a factor with increase injuries beyond the baseline rate.

I need to combine these factors and I don’t feel confident about the results at all, but that’s why I’m asking for help. Using the benchmarks from the two articles, a pitcher gets one injury factor for:

  • Throwing over 93 mph.
  • Having two or more career arm injuries.
  • Over 120 accumulated IL days with a bonus point for over 460 days.

And here are the 2019 starters (min 10 GS) grouped by the total injury factors.

Injury Factors for 2019 Starters
Name Age FBv Total IL Days On IL for Arm Velo Total IL Arm Factors
Charlie Morton 36 94.4 551 4 1 2 1 4
Homer Bailey 34 93.0 626 8 1 2 1 4
Nathan Eovaldi 30 97.5 470 5 1 2 1 4
Yu Darvish 33 94.2 492 5 1 2 1 4
Zack Wheeler 30 96.7 460 5 1 2 1 4
Adam Wainwright 38 89.9 618 4 0 2 1 3
Andrew Cashner 33 93.9 375 4 1 1 1 3
Brett Anderson 32 90.8 918 6 0 2 1 3
Carlos Carrasco 33 93.5 432 5 1 1 1 3
Chris Sale 31 93.2 121 4 1 1 1 3
Clay Buchholz 35 89.5 717 4 0 2 1 3
Gerrit Cole 29 97.2 143 4 1 1 1 3
Hyun-Jin Ryu 류현진 33 90.6 558 4 0 2 1 3
Jason Vargas 37 84.3 657 3 0 2 1 3
Martin Perez 29 94.1 377 5 1 1 1 3
Matt Harvey 31 93.2 433 4 1 1 1 3
Michael Pineda 31 92.6 511 5 0 2 1 3
Rich Hill 40 90.3 667 6 0 2 1 3
Stephen Strasburg 31 93.9 421 6 1 1 1 3
Steven Matz 29 93.4 244 5 1 1 1 3
Vince Velasquez 28 94.1 144 4 1 1 1 3
Aaron Sanchez 27 93.6 299 0 1 1 0 2
Andrew Heaney 29 92.5 419 4 0 1 1 2
Anibal Sanchez 36 90.5 427 5 0 1 1 2
Anthony DeSclafani 30 94.7 318 1 1 1 0 2
Chris Bassitt 31 93.5 290 2 1 1 0 2
Clayton Kershaw 32 90.4 217 3 0 1 1 2
Cole Hamels 36 91.4 182 4 0 1 1 2
Danny Duffy 31 92.4 414 7 0 1 1 2
David Price 34 92.0 199 4 0 1 1 2
Dinelson Lamet 27 96.1 289 2 1 1 0 2
Drew Smyly 31 91.2 355 3 0 1 1 2
Dylan Covey 28 94.4 131 2 1 1 0 2
Eduardo Rodriguez 27 93.1 162 0 1 1 0 2
Edwin Jackson 36 93.4 148 2 1 1 0 2
Felix Hernandez 34 89.6 313 4 0 1 1 2
Frankie Montas 27 96.6 183 0 1 1 0 2
Ivan Nova 33 92.4 299 4 0 1 1 2
Jacob deGrom 32 96.9 32 3 1 0 1 2
Jake Arrieta 34 92.5 140 3 0 1 1 2
James Paxton 31 95.5 361 2 1 1 0 2
Jhoulys Chacin 32 90 300 3 0 1 1 2
Jon Gray 28 96.1 136 0 1 1 0 2
Jordan Zimmermann 34 90.5 289 3 0 1 1 2
Jose Urena 28 95.9 124 1 1 1 0 2
Kevin Gausman 29 94 117 3 1 0 1 2
Lance Lynn 33 94.2 249 2 1 1 0 2
Michael Wacha 28 93.1 227 2 1 1 0 2
Mike Foltynewicz 28 94.9 84 3 1 0 1 2
Mike Minor 32 92.6 397 3 0 1 1 2
Noah Syndergaard 27 97.7 213 0 1 1 0 2
Sonny Gray 30 93.3 96 3 1 0 1 2
Tyler Glasnow 26 97 155 2 1 1 0 2
Zach Eflin 26 93.6 122 1 1 1 0 2
Aaron Brooks 30 92 183 0 0 1 0 1
Aaron Nola 27 92.9 143 2 0 1 0 1
Adrian Houser 27 94.4 0 0 1 0 0 1
Antonio Senzatela 25 93.7 29 1 1 0 0 1
Blake Snell 27 95.6 79 2 1 0 0 1
Brad Keller 24 93.4 0 0 1 0 0 1
Brad Peacock 32 92.2 257 2 0 1 0 1
Brandon Woodruff 27 96.3 57 0 1 0 0 1
Brendan McKay 24 93.7 0 0 1 0 0 1
Cal Quantrill 25 94.5 0 0 1 0 0 1
CC Sabathia 39 89.2 364 1 0 1 0 1
Chase Anderson 32 93.4 96 1 1 0 0 1
Chi Chi Gonzalez 28 92.2 182 1 0 1 0 1
Chris Archer 31 94.1 92 1 1 0 0 1
Chris Paddack 24 93.9 0 0 1 0 0 1
Clayton Richard 36 90.4 370 2 0 1 0 1
Dakota Hudson 25 93.7 0 0 1 0 0 1
Daniel Norris 27 90.8 357 0 0 1 0 1
David Hess 26 93 0 0 1 0 0 1
Domingo German 27 93.6 25 0 1 0 0 1
Dylan Cease 24 96.5 0 0 1 0 0 1
German Marquez 25 95.5 38 1 1 0 0 1
Glenn Sparkman 28 93.5 89 0 1 0 0 1
Griffin Canning 24 93.9 53 2 1 0 0 1
J.A. Happ 37 91.3 263 2 0 1 0 1
Jack Flaherty 24 93.9 0 0 1 0 0 1
Jeff Hoffman 27 93.7 31 1 1 0 0 1
Jeff Samardzija 35 91.9 139 2 0 1 0 1
Jerad Eickhoff 29 89.5 284 1 0 1 0 1
Jon Lester 36 90.3 162 0 0 1 0 1
Jordan Lyles 29 92.6 252 1 0 1 0 1
Justin Verlander 37 94.7 69 1 1 0 0 1
Kyle Gibson 32 93.3 57 1 1 0 0 1
Lucas Giolito 25 94.3 30 0 1 0 0 1
Luis Castillo 27 96.5 0 0 1 0 0 1
Luke Weaver 26 93.9 117 1 1 0 0 1
Madison Bumgarner 30 91.4 153 0 0 1 0 1
Marcus Stroman 29 92.5 217 1 0 1 0 1
Masahiro Tanaka 31 91.5 157 2 0 1 0 1
Max Fried 26 93.8 52 0 1 0 0 1
Max Scherzer 35 94.9 64 1 1 0 0 1
Mike Clevinger 29 95.5 79 0 1 0 0 1
Mike Soroka 22 92.5 129 2 0 1 0 1
Miles Mikolas 31 93.6 0 0 1 0 0 1
Mitch Keller 24 95.4 0 0 1 0 0 1
Pablo Lopez 24 93.6 108 2 1 0 0 1
Patrick Corbin 30 91.9 272 2 0 1 0 1
Reynaldo Lopez 26 95.5 14 0 1 0 0 1
Ross Detwiler 34 91.4 165 1 0 1 0 1
Sandy Alcantara 24 95.6 0 0 1 0 0 1
Shane Bieber 25 93.1 0 0 1 0 0 1
Spencer Turnbull 27 93.8 32 1 1 0 0 1
Taylor Clarke 27 93.7 16 0 1 0 0 1
Trevor Bauer 29 94.6 38 0 1 0 0 1
Tyler Beede 27 94.3 0 0 1 0 0 1
Tyler Mahle 25 93.3 33 0 1 0 0 1
Tyler Skaggs 28 91.4 430 2 0 1 0 1
Walker Buehler 25 96.6 16 0 1 0 0 1
Yonny Chirinos 26 93.9 81 1 1 0 0 1
Zach Davies 27 88.5 120 2 0 1 0 1
Zach Plesac 25 94 0 0 1 0 0 1
Zack Greinke 36 90 188 1 0 1 0 1
Aaron Civale 25 92.6 0 0 0 0 0 0
Adam Plutko 28 91.1 0 0 0 0 0 0
Alex Young 26 89.3 0 0 0 0 0 0
Ariel Jurado 24 92.4 0 0 0 0 0 0
Asher Wojciechowski 31 91.6 0 0 0 0 0 0
Caleb Smith 28 91.6 117 1 0 0 0 0
Dallas Keuchel 32 88.4 63 0 0 0 0 0
Dario Agrazal 25 91.2 0 0 0 0 0 0
Dereck Rodriguez 28 90.6 7 0 0 0 0 0
Dillon Peters 27 91.1 0 0 0 0 0 0
Dylan Bundy 27 91.2 30 1 0 0 0 0
Elieser Hernandez 25 90.6 53 0 0 0 0 0
Eric Lauer 25 91.9 30 1 0 0 0 0
Erick Fedde 27 92.3 88 2 0 0 0 0
Gio Gonzalez 34 89.3 80 2 0 0 0 0
Jacob Waguespack 26 91.6 35 1 0 0 0 0
Jaime Barria 23 91.7 0 0 0 0 0 0
Jake Odorizzi 30 92.9 75 0 0 0 0 0
Jakob Junis 27 91.5 13 0 0 0 0 0
Joe Musgrove 27 92.4 76 2 0 0 0 0
Joey Lucchesi 27 90.2 36 0 0 0 0 0
John Means 27 91.8 24 2 0 0 0 0
Jordan Yamamoto 24 91.5 27 1 0 0 0 0
Jose Berrios 26 92.8 0 0 0 0 0 0
Jose Quintana 31 91.4 0 0 0 0 0 0
Jose Suarez 22 91.8 0 0 0 0 0 0
Julio Teheran 29 89.7 28 0 0 0 0 0
Kenta Maeda 32 92.1 37 0 0 0 0 0
Kyle Freeland 27 91.9 51 0 0 0 0 0
Kyle Hendricks 30 86.9 66 1 0 0 0 0
Marco Gonzales 28 88.9 15 0 0 0 0 0
Matthew Boyd 29 92 0 0 0 0 0 0
Merrill Kelly 켈리 31 91.9 0 0 0 0 0 0
Mike Fiers 35 90.4 11 0 0 0 0 0
Mike Leake 32 88.4 51 1 0 0 0 0
Nick Margevicius 24 88.3 0 0 0 0 0 0
Peter Lambert 23 92.7 0 0 0 0 0 0
Rick Porcello 31 90.5 27 1 0 0 0 0
Robbie Ray 28 92.4 94 0 0 0 0 0
Ryan Yarbrough 28 88.2 0 0 0 0 0 0
Shaun Anderson 25 92.6 16 0 0 0 0 0
Steven Brault 28 92 31 1 0 0 0 0
Tanner Roark 33 92.1 0 0 0 0 0 0
Trent Thornton 26 92.9 11 1 0 0 0 0
Trevor Richards 27 90.9 0 0 0 0 0 0
Trevor Williams 28 91.3 33 0 0 0 0 0
Wade Miley 33 90.5 83 1 0 0 0 0
Yusei Kikuchi 29 92.5 0 0 0 0 0 0
Zac Gallen 24 92.9 0 0 0 0 0 0

What seems off?

Two areas of exploration I see from just putting words to the ideas are age and recent injuries. I just need to make sure age doesn’t have a greater effect than is already factored in. Second, Carlie Morton near the top intrigues me. I wonder if a IL recency factor needs to be added in. I know that the two aren’t the only questions, but they’ll keep me busy for a bit. What else is missing and can be explored? Let’s find as many answers to this to pitcher injuries.

 

 

Append #1: Aging

I took all the Steamer Projections and look how it did at projecting IP and stats for different ages. I didn’t find much if anything. First is how the projections held up for players under and over 30 (projected GS/G >= .5 and IP >= 10)

Actual Minus Projected Stats
Age IP ERA WHIP K_9 BB_9
Under 30 -10.4 0.44 0.04 0.31 0.15
30 and Over -15.4 0.30 0.03 0.12 0.14

The older starters underperformed their projections by five innings but generally overperformed in the talent stats when compared to the Younger hitters.

Innings: Actual Minus Innings Projected Grouped by Age

Rate Stats: Actual Minus Innings Projected Grouped by Age

I sort of see some trends … maybe.

6/19/20 update: While working with the Il days grouped by total days and the past two seasons, I found no signs that age was not properly accounted for.

Append #2: Previous Durability

Starts in Previous Two Seasons
Previous Two GS IP ERA WHIP K_9 BB_9 Count
>= 60 -12.4 0.08 0.00 0.14 0.03 432
50 to 59 -11.2 0.53 0.07 0.25 0.24 502
40 to 49 -4.9 0.68 0.10 0.38 0.31 839
30 to 39 -3.5 0.73 0.10 0.41 0.73 2597
20 to 29 3.7 0.96 0.13 0.40 0.88 3357

The durable pitchers lose a few more innings but almost match their projections. It’ time to make a Morton clone. Years of injuries but a recent clean slate.

6/19/20 Update: I’ve been cutting and dicing the data based on the total IL days and the ones accumulated over the past two seasons. I ran the data while accounting for age. Age doesn’t seem to be an issue. Here is the most simplified data at this point:

Starter Production Based on Recent & Total IL Days
Total IL Last 2 IL IP ERA WHIP K_9 BB_9
120 or less <= 30 -8 0.32 0.03 0.36 0.06
> 30 -21 0.48 0.05 0.03 0.38
Over 120 <= 30 -17 0.24 0.01 0.13 -0.01
> 30 -15 0.57 0.07 0.18 0.26

While these starters with over 120 career IL perform worse, being healthy over the past two seasons seems to stop a decline in talent. Now, I just picked 30 days out of thin air. My next step is to see if there is a better designation point.

Update: And 30 days was a damn fine guess. I’m not sure where to go next.





 

Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

3 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments
William Wallacemember
3 years ago

Jeff, this is interesting research. Two thoughts: I think the injury factors would be more useful for fantasy if playing time impact were separated from effectiveness (should I expect Ryu to be excellent whenever he isn’t on IL, or not?), and then for playing time and effectiveness, it would help to assess the independence of each injury factor and give each factor it’s appropriate weighting. That would help a fantasy player make an educated guess about the riskiness of each pitcher.

Thanks for doing all this work!

0
Jeff Zimmermanmember
3 years ago
Reply to  William Wallace

I like the idea of splitting apart more aging vs playing time.

I’m on it for an article early next week.

0